| Abstrakt: |
Text classification is a basic task in natural language processing, which has important applications in sentiment analysis, news classification and other fields. Compared with traditional machine learning and deep learning models, prompt learning can construct prompts for text classification in the case of insufficient data. In recent years, the emergence of GPT-3 has promoted the development of cue learning methods, and has made significant progress in the field of text classification. Firstly, this paper briefly combs the process of previous text classification methods and analyzes their existing problems and shortcomings. Secondly, it expounds the development process of cue learning and the method of constructing cue templates, and introduces and summarizes the research and results of cue learning methods for text classification. Finally, the development trend and difficulties to be further studied in the field of text classification are summarized and prospected. [ABSTRACT FROM AUTHOR] |
